Logs Data Extraction

WhatsApp to CRM: Extracting Data from Photos with Vision AI

5 min read Engineering Guide

The Operational Bottleneck: Small businesses run on efficiency, but most founders still spend Sunday night manually typing data from receipts, invoices, or handwritten field notes into their CRM/ERP.

With "Vision" capabilities in modern LLMs (GPT-4o, Claude 3.5 Sonnet), we can eliminate this entirely. We can treat an image as a structured database.

The Workflow

We use WhatsApp because it's the interface of least resistance. You don't need to build a custom mobile app for your operations team.

  • Input: Photo sent to Twilio (WhatsApp API).
  • Processing: Image passed to GPT-4o-Vision.
  • Extraction: JSON Schema enforced extraction.
  • Output: CRM (HubSpot/Salesforce) record created.

Reliability via "Reflexion"

OCR is notoriously fickle with handwriting. To make this production-ready, we implement a "Confidence Check" step.

// Prompt Strategy: Reflexion
"Analyze the image. Extract the 'Total Amount' and 'Vendor Name'.

CRITICAL: If the handwriting is illegible or ambiguous, return null for that field and set 'requires_human_review' to true.

Do not guess."

If `requires_human_review` is true, the system pings a Slack channel with the image, asking a human to confirm just that one field. This "Human-in-the-Loop" design ensures 100% data integrity while automating 95% of the work.

Use Cases

  1. Expense Management: Snap photo of receipt -> QuickBooks.
  2. Field Sales: Snap photo of business card -> HubSpot Contact.
  3. Logistics: Snap photo of Bill of Lading -> ERP Inventory Update.

Automate your structured data entry.

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